Reliability and Accuracy of the AMP 331 for Activity Monitoring and Energy Expenditure Prediction in Young Adults.

BACKGROUND A new triaxial accelerometer (AMP 331) provides a novel approach to understanding free-living activity through its ability to measure real time speed, cadence, and step length. This study examined the reliability and accuracy of the AMP 331, along with construction of prediction equations for oxygen consumption and energy cost. METHODS Young adult volunteers (n = 41) wearing two AMP units walked and ran on a treadmill with energy cost data simultaneously collected through indirect calorimetry. RESULTS Statistically significant differences exist in inter-AMP unit reliability for speed and step length and in accuracy between the AMP units and criterion measures for speed, oxygen consumption, and energy cost. However, the differences in accuracy for speed were very small during walking (≤ 0.16 km/h) and not clinically relevant. Prediction equations constructed for walking oxygen uptake and energy expenditure demonstrated R2 between 0.76 to 0.90 and between subject deviations were 1.53 mL O2 · kg-1 · min-1 and 0.43 kcal/min. CONCLUSIONS In young adults, the AMP 331 is acceptable for monitoring walking speeds and the output can be used in predicting energy cost during walking but not running.

[1]  K R Westerterp,et al.  Validation of the Tracmor triaxial accelerometer system for walking. , 2001, Medicine and science in sports and exercise.

[2]  M. Feinleib National Center for Health Statistics (NCHS) , 2005 .

[3]  Ann V Rowlands,et al.  Validation of the RT3 triaxial accelerometer for the assessment of physical activity. , 2004, Medicine and science in sports and exercise.

[4]  G. Welk,et al.  Reliability of accelerometry-based activity monitors: a generalizability study. , 2004, Medicine and science in sports and exercise.

[5]  B. Steele,et al.  Bodies in motion: monitoring daily activity and exercise with motion sensors in people with chronic pulmonary disease. , 2003, Journal of rehabilitation research and development.

[6]  P. D. Watson,et al.  Validity of the computer science and applications (CSA) activity monitor in children. , 1998, Medicine and science in sports and exercise.

[7]  D H Nielsen,et al.  Clinical determination of energy cost and walking velocity via stopwatch or speedometer cane and conversion graphs. , 1982, Physical therapy.

[8]  Catrine Tudor-Locke,et al.  Comparison of pedometer and accelerometer accuracy under controlled conditions. , 2003, Medicine and science in sports and exercise.

[9]  Ack,et al.  LOWER-EXTREMITY FUNCTION IN PERSONS OVER THE AGE OF 70 YEARS AS A PREDICTOR OF SUBSEQUENT DISABILITY , 2001 .

[10]  Wim H. M. Saris,et al.  Measuring Physical Activity and Energy Expenditure , 1996 .

[11]  D. Mannino,et al.  Leisure-time physical activity patterns among US adults with asthma. , 2003, Chest.

[12]  Nigel O'Brian,et al.  Generalizability Theory I , 2003 .

[13]  S. Blair,et al.  A comparative evaluation of three accelerometry-based physical activity monitors. , 2000, Medicine and science in sports and exercise.

[14]  P. Freedson,et al.  Compliance with physical activity guidelines: prevalence in a population of children and youth. , 2002, Annals of epidemiology.

[15]  A HENSCHEL,et al.  Maximal oxygen intake as an objective measure of cardio-respiratory performance. , 1955, Journal of applied physiology.

[16]  U. Ekelund,et al.  Physical activity levels and patterns of 9- and 15-yr-old European children. , 2004, Medicine and science in sports and exercise.

[17]  J. Sallis Measuring Physical Activity and Energy Expenditure , 1996 .